WEBVTT 00:00.000 --> 00:03.440 The following is a conversation with Kevin Scott, 00:03.440 --> 00:06.080 the CTO of Microsoft. 00:06.080 --> 00:08.560 Before that, he was the senior vice president 00:08.560 --> 00:11.080 of engineering and operations at LinkedIn, 00:11.080 --> 00:13.520 and before that, he oversaw mobile ads 00:13.520 --> 00:14.960 engineering at Google. 00:15.960 --> 00:19.000 He also has a podcast called Behind the Tech 00:19.000 --> 00:21.880 with Kevin Scott, which I'm a fan of. 00:21.880 --> 00:24.280 This was a fun and wide ranging conversation 00:24.280 --> 00:26.680 that covered many aspects of computing. 00:26.680 --> 00:28.840 It happened over a month ago, 00:28.840 --> 00:31.000 before the announcement of Microsoft's investment 00:31.000 --> 00:34.440 OpenAI that a few people have asked me about. 00:34.440 --> 00:38.120 I'm sure there'll be one or two people in the future 00:38.120 --> 00:41.400 that'll talk with me about the impact of that investment. 00:42.280 --> 00:45.440 This is the Artificial Intelligence podcast. 00:45.440 --> 00:47.680 If you enjoy it, subscribe on YouTube, 00:47.680 --> 00:49.440 give it five stars on iTunes, 00:49.440 --> 00:50.960 support it on a Patreon, 00:50.960 --> 00:53.000 or simply connect with me on Twitter, 00:53.000 --> 00:57.680 at Lex Freedman, spelled FRIDMAM. 00:57.680 --> 00:59.240 And I'd like to give a special thank you 00:59.240 --> 01:01.960 to Tom and Elanti Bighausen 01:01.960 --> 01:04.600 for their support of the podcast on Patreon. 01:04.600 --> 01:06.080 Thanks Tom and Elanti. 01:06.080 --> 01:08.400 Hope I didn't mess up your last name too bad. 01:08.400 --> 01:10.520 Your support means a lot, 01:10.520 --> 01:13.480 and inspires me to keep this series going. 01:13.480 --> 01:18.160 And now, here's my conversation with Kevin Scott. 01:18.160 --> 01:20.760 You've described yourself as a kid in a candy store 01:20.760 --> 01:23.000 at Microsoft because of all the interesting projects 01:23.000 --> 01:24.200 that are going on. 01:24.200 --> 01:28.000 Can you try to do the impossible task 01:28.000 --> 01:31.760 and give a brief whirlwind view 01:31.760 --> 01:34.520 of all the spaces that Microsoft is working in? 01:35.520 --> 01:37.440 Both research and product. 01:37.440 --> 01:42.440 If you include research, it becomes even more difficult. 01:46.480 --> 01:48.880 So, I think broadly speaking, 01:48.880 --> 01:53.720 Microsoft's product portfolio includes everything 01:53.720 --> 01:56.920 from big cloud business, 01:56.920 --> 01:59.360 like a big set of SaaS services. 01:59.360 --> 02:01.720 We have sort of the original, 02:01.720 --> 02:05.560 or like some of what are among the original 02:05.560 --> 02:09.640 productivity software products that everybody uses. 02:09.640 --> 02:11.200 We have an operating system business. 02:11.200 --> 02:13.560 We have a hardware business 02:13.560 --> 02:17.240 where we make everything from computer mice 02:17.240 --> 02:20.760 and headphones to high end, 02:20.760 --> 02:23.520 high end personal computers and laptops. 02:23.520 --> 02:27.680 We have a fairly broad ranging research group 02:27.680 --> 02:29.680 where we have people doing everything 02:29.680 --> 02:31.880 from economics research. 02:31.880 --> 02:35.920 So, there's this really smart young economist, 02:35.920 --> 02:39.760 Glenn Weil, who like my group works with a lot, 02:39.760 --> 02:42.880 who's doing this research on these things 02:42.880 --> 02:45.120 called radical markets. 02:45.120 --> 02:48.120 Like he's written an entire technical book 02:48.120 --> 02:51.120 about this whole notion of radical markets. 02:51.120 --> 02:53.520 So, like the research group sort of spans from that 02:53.520 --> 02:56.840 to human computer interaction, to artificial intelligence. 02:56.840 --> 03:01.040 And we have GitHub, we have LinkedIn. 03:01.040 --> 03:05.800 We have a search advertising and news business 03:05.800 --> 03:07.360 and like probably a bunch of stuff 03:07.360 --> 03:11.240 that I'm embarrassingly not recounting in this list. 03:11.240 --> 03:12.920 On gaming to Xbox and so on, right? 03:12.920 --> 03:14.120 Yeah, gaming for sure. 03:14.120 --> 03:17.320 Like I was having a super fun conversation 03:17.320 --> 03:19.520 this morning with Phil Spencer. 03:19.520 --> 03:21.280 So, when I was in college, 03:21.280 --> 03:25.560 there was this game that Lucas Arts made 03:25.560 --> 03:27.600 called Day of the Tentacle, 03:27.600 --> 03:30.160 that my friends and I played forever. 03:30.160 --> 03:33.920 And like we're doing some interesting collaboration now 03:33.920 --> 03:37.920 with the folks who made Day of the Tentacle. 03:37.920 --> 03:40.840 And I was like completely nerding out with Tim Schaeffer, 03:40.840 --> 03:43.880 like the guy who wrote Day of the Tentacle this morning, 03:43.880 --> 03:45.840 just a complete fanboy, 03:45.840 --> 03:49.880 which you know, sort of it like happens a lot. 03:49.880 --> 03:53.320 Like, you know, Microsoft has been doing so much stuff 03:53.320 --> 03:56.000 at such breadth for such a long period of time 03:56.000 --> 03:59.680 that, you know, like being CTO, 03:59.680 --> 04:02.200 like most of the time my job is very, very serious 04:02.200 --> 04:05.640 and sometimes that like I get caught up 04:05.640 --> 04:09.200 in like how amazing it is 04:09.200 --> 04:11.520 to be able to have the conversations 04:11.520 --> 04:14.640 that I have with the people I get to have them with. 04:14.640 --> 04:17.040 You had to reach back into the sentimental 04:17.040 --> 04:21.640 and what's the radical markets and the economics? 04:21.640 --> 04:24.760 So the idea with radical markets is like, 04:24.760 --> 04:29.760 can you come up with new market based mechanisms to, 04:32.320 --> 04:33.800 you know, I think we have this, 04:33.800 --> 04:35.240 we're having this debate right now, 04:35.240 --> 04:40.040 like does capitalism work, like free markets work? 04:40.040 --> 04:43.000 Can the incentive structures 04:43.000 --> 04:46.360 that are built into these systems produce outcomes 04:46.360 --> 04:51.360 that are creating sort of equitably distributed benefits 04:51.560 --> 04:53.520 for every member of society? 04:55.400 --> 04:58.720 You know, and I think it's a reasonable set of questions 04:58.720 --> 04:59.560 to be asking. 04:59.560 --> 05:02.160 And so what Glenn, and so like, you know, 05:02.160 --> 05:04.400 one mode of thought there, like if you have doubts 05:04.400 --> 05:06.720 that the markets are actually working, 05:06.720 --> 05:08.560 you can sort of like tip towards like, 05:08.560 --> 05:10.800 okay, let's become more socialist 05:10.800 --> 05:14.240 and like have central planning and governments 05:14.240 --> 05:15.800 or some other central organization 05:15.800 --> 05:18.280 is like making a bunch of decisions 05:18.280 --> 05:22.040 about how sort of work gets done 05:22.040 --> 05:25.400 and like where the investments 05:25.400 --> 05:28.880 and where the outputs of those investments get distributed. 05:28.880 --> 05:32.160 Glenn's notion is like lean more 05:32.160 --> 05:35.800 into like the market based mechanism. 05:35.800 --> 05:37.920 So like for instance, 05:37.920 --> 05:39.600 this is one of the more radical ideas, 05:39.600 --> 05:44.600 like suppose that you had a radical pricing mechanism 05:45.160 --> 05:47.120 for assets like real estate 05:47.120 --> 05:52.120 where you could be bid out of your position 05:53.600 --> 05:58.600 in your home, you know, for instance. 05:58.720 --> 06:01.120 So like if somebody came along and said, 06:01.120 --> 06:04.400 you know, like I can find higher economic utility 06:04.400 --> 06:05.760 for this piece of real estate 06:05.760 --> 06:08.720 that you're running your business in, 06:08.720 --> 06:13.040 like then like you either have to, you know, 06:13.040 --> 06:16.440 sort of bid to sort of stay 06:16.440 --> 06:19.960 or like the thing that's got the higher economic utility, 06:19.960 --> 06:21.440 you know, sort of takes over the asset 06:21.440 --> 06:23.720 and which would make it very difficult 06:23.720 --> 06:27.600 to have the same sort of rent seeking behaviors 06:27.600 --> 06:29.000 that you've got right now 06:29.000 --> 06:34.000 because like if you did speculative bidding, 06:34.000 --> 06:39.000 like you would very quickly like lose a whole lot of money. 06:40.440 --> 06:43.520 And so like the prices of the assets would be sort of 06:43.520 --> 06:47.600 like very closely indexed to like the value 06:47.600 --> 06:49.720 that they can produce. 06:49.720 --> 06:52.680 And like because like you'd have this sort of real time 06:52.680 --> 06:55.320 mechanism that would force you to sort of mark the value 06:55.320 --> 06:56.800 of the asset to the market, 06:56.800 --> 06:58.560 then it could be taxed appropriately. 06:58.560 --> 07:00.400 Like you couldn't sort of sit on this thing and say, 07:00.400 --> 07:03.040 oh, like this house is only worth 10,000 bucks 07:03.040 --> 07:06.600 when like everything around it is worth 10 million. 07:06.600 --> 07:07.440 That's really interesting. 07:07.440 --> 07:08.720 So it's an incentive structure 07:08.720 --> 07:13.200 that where the prices match the value much better. 07:13.200 --> 07:14.040 Yeah. 07:14.040 --> 07:16.320 And Glenn does a much, much better job than I do 07:16.320 --> 07:18.920 at selling and I probably picked the world's worst example, 07:18.920 --> 07:20.360 you know, and, and, and, but like, 07:20.360 --> 07:24.520 and it's intentionally provocative, you know, 07:24.520 --> 07:26.480 so like this whole notion, like I, you know, 07:26.480 --> 07:28.920 like I'm not sure whether I like this notion 07:28.920 --> 07:31.120 that like we can have a set of market mechanisms 07:31.120 --> 07:35.360 where I could get bid out of, out of my property, you know, 07:35.360 --> 07:37.680 but, but, you know, like if you're thinking about something 07:37.680 --> 07:42.480 like Elizabeth Warren's wealth tax, for instance, 07:42.480 --> 07:45.600 like you would have, I mean, it'd be really interesting 07:45.600 --> 07:50.080 in like how you would actually set the price on the assets. 07:50.080 --> 07:52.040 And like you might have to have a mechanism like that 07:52.040 --> 07:54.160 if you put a tax like that in place. 07:54.160 --> 07:56.440 It's really interesting that that kind of research, 07:56.440 --> 07:59.800 at least tangentially touching Microsoft research. 07:59.800 --> 08:00.640 Yeah. 08:00.640 --> 08:02.560 So if you're really thinking broadly, 08:02.560 --> 08:07.560 maybe you can speak to this connects to AI. 08:08.400 --> 08:10.680 So we have a candidate, Andrew Yang, 08:10.680 --> 08:13.480 who kind of talks about artificial intelligence 08:13.480 --> 08:16.640 and the concern that people have about, you know, 08:16.640 --> 08:19.000 automations impact on society. 08:19.000 --> 08:22.680 And arguably Microsoft is at the cutting edge 08:22.680 --> 08:25.040 of innovation in all these kinds of ways. 08:25.040 --> 08:27.080 And so it's pushing AI forward. 08:27.080 --> 08:30.040 How do you think about combining all our conversations 08:30.040 --> 08:32.840 together here with radical markets and socialism 08:32.840 --> 08:37.520 and innovation in AI that Microsoft is doing? 08:37.520 --> 08:42.520 And then Andrew Yang's worry that that will, 08:43.520 --> 08:46.840 that will result in job loss for the lower and so on. 08:46.840 --> 08:47.680 How do you think about that? 08:47.680 --> 08:51.160 I think it's sort of one of the most important questions 08:51.160 --> 08:55.320 in technology, like maybe even in society right now 08:55.320 --> 09:00.320 about how is AI going to develop over the course 09:00.720 --> 09:02.000 of the next several decades 09:02.000 --> 09:03.600 and like what's it gonna be used for 09:03.600 --> 09:06.560 and like what benefits will it produce 09:06.560 --> 09:08.520 and what negative impacts will it produce 09:08.520 --> 09:13.520 and you know, who gets to steer this whole thing? 09:13.720 --> 09:16.320 You know, I'll say at the highest level, 09:17.240 --> 09:22.240 one of the real joys of getting to do what I do at Microsoft 09:22.240 --> 09:27.240 is Microsoft has this heritage as a platform company. 09:27.560 --> 09:31.040 And so, you know, like Bill has this thing 09:31.040 --> 09:32.880 that he said a bunch of years ago 09:32.880 --> 09:36.440 where the measure of a successful platform 09:36.440 --> 09:39.800 is that it produces far more economic value 09:39.800 --> 09:41.840 for the people who build on top of the platform 09:41.840 --> 09:46.840 than is created for the platform owner or builder. 09:47.320 --> 09:50.920 And I think we have to think about AI that way. 09:50.920 --> 09:55.920 Like it has to be a platform that other people can use 09:56.280 --> 10:01.280 to build businesses, to fulfill their creative objectives, 10:01.280 --> 10:04.640 to be entrepreneurs, to solve problems that they have 10:04.640 --> 10:07.680 in their work and in their lives. 10:07.680 --> 10:11.960 It can't be a thing where there are a handful of companies 10:11.960 --> 10:16.440 sitting in a very small handful of cities geographically 10:16.440 --> 10:19.120 who are making all the decisions 10:19.120 --> 10:24.120 about what goes into the AI and like, 10:24.240 --> 10:26.920 and then on top of like all this infrastructure, 10:26.920 --> 10:31.000 then build all of the commercially valuable uses for it. 10:31.000 --> 10:34.400 So like, I think like that's bad from a, you know, 10:34.400 --> 10:36.520 sort of, you know, economics 10:36.520 --> 10:39.720 and sort of equitable distribution of value perspective, 10:39.720 --> 10:42.080 like, you know, sort of back to this whole notion of, 10:42.080 --> 10:44.560 you know, like, do the markets work? 10:44.560 --> 10:47.600 But I think it's also bad from an innovation perspective 10:47.600 --> 10:51.360 because like I have infinite amounts of faith 10:51.360 --> 10:53.880 in human beings that if you, you know, 10:53.880 --> 10:58.280 give folks powerful tools, they will go do interesting things. 10:58.280 --> 11:02.320 And it's more than just a few tens of thousands of people 11:02.320 --> 11:03.360 with the interesting tools, 11:03.360 --> 11:05.400 it should be millions of people with the tools. 11:05.400 --> 11:07.200 So it's sort of like, you know, 11:07.200 --> 11:10.200 you think about the steam engine 11:10.200 --> 11:13.800 and the late 18th century, like it was, you know, 11:13.800 --> 11:16.800 maybe the first large scale substitute for human labor 11:16.800 --> 11:19.120 that we've built like a machine. 11:19.120 --> 11:21.680 And, you know, in the beginning, 11:21.680 --> 11:23.520 when these things are getting deployed, 11:23.520 --> 11:28.320 the folks who got most of the value from the steam engines 11:28.320 --> 11:30.160 were the folks who had capital 11:30.160 --> 11:31.600 so they could afford to build them. 11:31.600 --> 11:34.720 And like they built factories around them in businesses 11:34.720 --> 11:38.680 and the experts who knew how to build and maintain them. 11:38.680 --> 11:42.880 But access to that technology democratized over time. 11:42.880 --> 11:47.040 Like now like an engine is not a, 11:47.040 --> 11:48.800 it's not like a differentiated thing. 11:48.800 --> 11:50.280 Like there isn't one engine company 11:50.280 --> 11:51.560 that builds all the engines 11:51.560 --> 11:53.120 and all of the things that use engines 11:53.120 --> 11:54.240 are made by this company. 11:54.240 --> 11:57.440 And like they get all the economics from all of that. 11:57.440 --> 11:59.320 Like, no, like fully demarcated. 11:59.320 --> 12:00.600 Like they're probably, you know, 12:00.600 --> 12:02.360 we're sitting here in this room 12:02.360 --> 12:03.680 and like even though they don't, 12:03.680 --> 12:05.280 they're probably things, you know, 12:05.280 --> 12:09.120 like the MIMS gyroscope that are in both of our, 12:09.120 --> 12:11.480 like there's like little engines, you know, 12:11.480 --> 12:14.520 sort of everywhere, they're just a component 12:14.520 --> 12:16.240 in how we build the modern world. 12:16.240 --> 12:17.680 Like AI needs to get there. 12:17.680 --> 12:20.200 Yeah, so that's a really powerful way to think. 12:20.200 --> 12:25.120 If we think of AI as a platform versus a tool 12:25.120 --> 12:27.600 that Microsoft owns as a platform 12:27.600 --> 12:30.120 that enables creation on top of it, 12:30.120 --> 12:31.520 that's the way to democratize it. 12:31.520 --> 12:34.200 That's really interesting actually. 12:34.200 --> 12:36.040 And Microsoft throughout its history 12:36.040 --> 12:38.240 has been positioned well to do that. 12:38.240 --> 12:41.640 And the, you know, the tieback to this radical markets thing, 12:41.640 --> 12:46.640 like the, so my team has been working with Glenn 12:47.800 --> 12:51.120 on this and Jaren Lanier actually. 12:51.120 --> 12:56.120 So Jaren is the like the sort of father of virtual reality. 12:56.440 --> 12:59.480 Like he's one of the most interesting human beings 12:59.480 --> 13:01.760 on the planet, like a sweet, sweet guy. 13:02.840 --> 13:07.120 And so Jaren and Glenn and folks in my team 13:07.120 --> 13:10.360 have been working on this notion of data as labor 13:10.360 --> 13:13.160 or like they call it data dignity as well. 13:13.160 --> 13:16.880 And so the idea is that if you, you know, 13:16.880 --> 13:18.600 again, going back to this, you know, 13:18.600 --> 13:20.800 sort of industrial analogy, 13:20.800 --> 13:23.560 if you think about data as the raw material 13:23.560 --> 13:27.640 that is consumed by the machine of AI 13:27.640 --> 13:30.560 in order to do useful things, 13:30.560 --> 13:34.400 then like we're not doing a really great job right now 13:34.400 --> 13:37.760 in having transparent marketplaces for valuing 13:37.760 --> 13:39.800 those data contributions. 13:39.800 --> 13:42.680 So like, and we all make them like explicitly, 13:42.680 --> 13:43.600 like you go to LinkedIn, 13:43.600 --> 13:46.160 you sort of set up your profile on LinkedIn, 13:46.160 --> 13:47.800 like that's an explicit contribution. 13:47.800 --> 13:49.480 Like, you know exactly the information 13:49.480 --> 13:50.720 that you're putting into the system. 13:50.720 --> 13:53.000 And like you put it there because you have 13:53.000 --> 13:55.520 some nominal notion of like what value 13:55.520 --> 13:56.640 you're going to get in return, 13:56.640 --> 13:57.720 but it's like only nominal. 13:57.720 --> 13:59.680 Like you don't know exactly what value 13:59.680 --> 14:02.040 you're getting in return, like services free, you know, 14:02.040 --> 14:04.600 like it's low amount of like perceived. 14:04.600 --> 14:06.680 And then you've got all this indirect contribution 14:06.680 --> 14:08.960 that you're making just by virtue of interacting 14:08.960 --> 14:13.160 with all of the technology that's in your daily life. 14:13.160 --> 14:16.120 And so like what Glenn and Jaren 14:16.120 --> 14:19.440 and this data dignity team are trying to do is like, 14:19.440 --> 14:22.240 can we figure out a set of mechanisms 14:22.240 --> 14:26.000 that let us value those data contributions 14:26.000 --> 14:28.200 so that you could create an economy 14:28.200 --> 14:31.480 and like a set of controls and incentives 14:31.480 --> 14:36.480 that would allow people to like maybe even in the limit 14:36.840 --> 14:38.880 like earn part of their living 14:38.880 --> 14:41.000 through the data that they're creating. 14:41.000 --> 14:42.680 And like you can sort of see it in explicit ways. 14:42.680 --> 14:46.000 There are these companies like Scale AI 14:46.000 --> 14:49.960 and like they're a whole bunch of them in China right now 14:49.960 --> 14:52.400 that are basically data labeling companies. 14:52.400 --> 14:54.560 So like you're doing supervised machine learning, 14:54.560 --> 14:57.400 you need lots and lots of label training data. 14:58.600 --> 15:01.440 And like those people are getting like who work 15:01.440 --> 15:03.600 for those companies are getting compensated 15:03.600 --> 15:06.360 for their data contributions into the system. 15:06.360 --> 15:07.720 And so... 15:07.720 --> 15:10.280 That's easier to put a number on their contribution 15:10.280 --> 15:11.960 because they're explicitly labeling data. 15:11.960 --> 15:12.800 Correct. 15:12.800 --> 15:14.360 But you're saying that we're all contributing data 15:14.360 --> 15:15.720 in different kinds of ways. 15:15.720 --> 15:19.640 And it's fascinating to start to explicitly try 15:19.640 --> 15:20.880 to put a number on it. 15:20.880 --> 15:22.600 Do you think that's possible? 15:22.600 --> 15:23.640 I don't know, it's hard. 15:23.640 --> 15:25.480 It really is. 15:25.480 --> 15:30.480 Because, you know, we don't have as much transparency 15:30.480 --> 15:35.480 as I think we need in like how the data is getting used. 15:37.240 --> 15:38.720 And it's, you know, super complicated. 15:38.720 --> 15:41.000 Like, you know, we, you know, 15:41.000 --> 15:42.880 I think as technologists sort of appreciate 15:42.880 --> 15:44.160 like some of the subtlety there. 15:44.160 --> 15:47.880 It's like, you know, the data, the data gets created 15:47.880 --> 15:51.400 and then it gets, you know, it's not valuable. 15:51.400 --> 15:56.000 Like the data exhaust that you give off 15:56.000 --> 15:58.480 or the, you know, the explicit data 15:58.480 --> 16:03.240 that I am putting into the system isn't valuable. 16:03.240 --> 16:05.160 It's super valuable atomically. 16:05.160 --> 16:08.360 Like it's only valuable when you sort of aggregate it together 16:08.360 --> 16:10.440 into, you know, sort of large numbers. 16:10.440 --> 16:11.960 It's true even for these like folks 16:11.960 --> 16:14.880 who are getting compensated for like labeling things. 16:14.880 --> 16:16.480 Like for supervised machine learning now, 16:16.480 --> 16:20.080 like you need lots of labels to train, you know, 16:20.080 --> 16:22.080 a model that performs well. 16:22.080 --> 16:24.440 And so, you know, I think that's one of the challenges. 16:24.440 --> 16:26.120 It's like, how do you, you know, 16:26.120 --> 16:28.000 how do you sort of figure out like 16:28.000 --> 16:31.480 because this data is getting combined in so many ways, 16:31.480 --> 16:33.880 like through these combinations, 16:33.880 --> 16:35.880 like how the value is flowing. 16:35.880 --> 16:38.520 Yeah, that's, that's fascinating. 16:38.520 --> 16:39.360 Yeah. 16:39.360 --> 16:41.880 And it's fascinating that you're thinking about this. 16:41.880 --> 16:44.160 And I wasn't even going into this competition 16:44.160 --> 16:48.200 expecting the breadth of research really 16:48.200 --> 16:50.600 that Microsoft broadly is thinking about. 16:50.600 --> 16:52.360 You are thinking about in Microsoft. 16:52.360 --> 16:57.360 So if we go back to 89 when Microsoft released Office 16:57.360 --> 17:00.920 or 1990 when they released Windows 3.0, 17:00.920 --> 17:04.960 how's the, in your view, 17:04.960 --> 17:07.280 I know you weren't there the entire, you know, 17:07.280 --> 17:09.760 through its history, but how has the company changed 17:09.760 --> 17:12.840 in the 30 years since as you look at it now? 17:12.840 --> 17:17.080 The good thing is it's started off as a platform company. 17:17.080 --> 17:19.960 Like it's still a platform company, 17:19.960 --> 17:22.640 like the parts of the business that are like thriving 17:22.640 --> 17:26.560 and most successful or those that are building platforms, 17:26.560 --> 17:29.000 like the mission of the company now is, 17:29.000 --> 17:30.120 the mission's changed. 17:30.120 --> 17:32.480 It's like changing a very interesting way. 17:32.480 --> 17:36.280 So, you know, back in 89.90, 17:36.280 --> 17:39.040 like they were still on the original mission, 17:39.040 --> 17:43.840 which was like put a PC on every desk and in every home. 17:43.840 --> 17:47.480 Like, and it was basically about democratizing access 17:47.480 --> 17:50.000 to this new personal computing technology, 17:50.000 --> 17:52.680 which when Bill started the company, 17:52.680 --> 17:57.680 integrated circuit microprocessors were a brand new thing 17:57.680 --> 18:00.120 and like people were building, you know, 18:00.120 --> 18:03.840 homebrew computers, you know, from kits, 18:03.840 --> 18:07.520 like the way people build ham radios right now. 18:08.520 --> 18:10.680 And I think this is sort of the interesting thing 18:10.680 --> 18:12.840 for folks who build platforms in general. 18:12.840 --> 18:16.840 Bill saw the opportunity there 18:16.840 --> 18:18.720 and what personal computers could do. 18:18.720 --> 18:20.440 And it was like, it was sort of a reach. 18:20.440 --> 18:21.680 Like you just sort of imagined 18:21.680 --> 18:23.880 like where things were, you know, 18:23.880 --> 18:24.880 when they started the company 18:24.880 --> 18:26.120 versus where things are now. 18:26.120 --> 18:29.400 Like in success, when you democratize a platform, 18:29.400 --> 18:31.000 it just sort of vanishes into the platform. 18:31.000 --> 18:32.480 You don't pay attention to it anymore. 18:32.480 --> 18:35.600 Like operating systems aren't a thing anymore. 18:35.600 --> 18:38.040 Like they're super important, like completely critical. 18:38.040 --> 18:41.760 And like, you know, when you see one, you know, fail, 18:41.760 --> 18:43.520 like you just, you sort of understand, 18:43.520 --> 18:45.320 but like, you know, it's not a thing where you're, 18:45.320 --> 18:47.920 you're not like waiting for, you know, 18:47.920 --> 18:50.480 the next operating system thing 18:50.480 --> 18:52.960 in the same way that you were in 1995, right? 18:52.960 --> 18:54.280 Like in 1995, like, you know, 18:54.280 --> 18:56.000 we had Rolling Stones on the stage 18:56.000 --> 18:57.600 with the Windows 95 roll out. 18:57.600 --> 18:59.320 Like it was like the biggest thing in the world. 18:59.320 --> 19:01.080 Everybody would like lined up for it 19:01.080 --> 19:03.400 the way that people used to line up for iPhone. 19:03.400 --> 19:05.120 But like, you know, eventually, 19:05.120 --> 19:07.160 and like this isn't necessarily a bad thing. 19:07.160 --> 19:09.000 Like it just sort of, you know, 19:09.000 --> 19:12.880 the success is that it's sort of, it becomes ubiquitous. 19:12.880 --> 19:14.800 It's like everywhere and like human beings 19:14.800 --> 19:16.640 when their technology becomes ubiquitous, 19:16.640 --> 19:18.240 they just sort of start taking it for granted. 19:18.240 --> 19:23.240 So the mission now that Satya rearticulated 19:23.640 --> 19:25.280 five plus years ago now 19:25.280 --> 19:27.360 when he took over as CEO of the company, 19:29.320 --> 19:33.480 our mission is to empower every individual 19:33.480 --> 19:37.760 and every organization in the world to be more successful. 19:39.200 --> 19:43.160 And so, you know, again, like that's a platform mission. 19:43.160 --> 19:46.320 And like the way that we do it now is different. 19:46.320 --> 19:48.680 It's like we have a hyperscale cloud 19:48.680 --> 19:51.680 that people are building their applications on top of. 19:51.680 --> 19:53.680 Like we have a bunch of AI infrastructure 19:53.680 --> 19:56.280 that people are building their AI applications on top of. 19:56.280 --> 20:01.280 We have, you know, we have a productivity suite of software 20:02.280 --> 20:05.800 like Microsoft Dynamics, which, you know, 20:05.800 --> 20:07.440 some people might not think is the sexiest thing 20:07.440 --> 20:10.040 in the world, but it's like helping people figure out 20:10.040 --> 20:12.720 how to automate all of their business processes 20:12.720 --> 20:16.800 and workflows and to, you know, like help those businesses 20:16.800 --> 20:19.120 using it to like grow and be more successful. 20:19.120 --> 20:24.120 So it's a much broader vision in a way now 20:24.240 --> 20:25.480 than it was back then. 20:25.480 --> 20:27.400 Like it was sort of very particular thing. 20:27.400 --> 20:29.280 And like now, like we live in this world 20:29.280 --> 20:31.320 where technology is so powerful 20:31.320 --> 20:36.320 and it's like such a basic fact of life 20:36.320 --> 20:39.760 that it, you know, that it both exists 20:39.760 --> 20:42.760 and is going to get better and better over time 20:42.760 --> 20:46.000 or at least more and more powerful over time. 20:46.000 --> 20:48.200 So like, you know, what you have to do as a platform player 20:48.200 --> 20:49.920 is just much bigger. 20:49.920 --> 20:50.760 Right. 20:50.760 --> 20:52.600 There's so many directions in which you can transform. 20:52.600 --> 20:55.160 You didn't mention mixed reality too. 20:55.160 --> 20:59.200 You know, that's probably early days 20:59.200 --> 21:00.680 or depends how you think of it. 21:00.680 --> 21:02.240 But if we think in a scale of centuries, 21:02.240 --> 21:04.120 it's the early days of mixed reality. 21:04.120 --> 21:04.960 Oh, for sure. 21:04.960 --> 21:08.280 And so yeah, with how it lands, 21:08.280 --> 21:10.600 the Microsoft is doing some really interesting work there. 21:10.600 --> 21:13.560 Do you touch that part of the effort? 21:13.560 --> 21:14.840 What's the thinking? 21:14.840 --> 21:17.640 Do you think of mixed reality as a platform too? 21:17.640 --> 21:18.480 Oh, sure. 21:18.480 --> 21:21.320 When we look at what the platforms of the future could be. 21:21.320 --> 21:23.880 So like fairly obvious that like AI is one, 21:23.880 --> 21:26.600 like you don't have to, I mean, like that's, 21:26.600 --> 21:29.160 you know, you sort of say it to like someone 21:29.160 --> 21:31.920 and you know, like they get it. 21:31.920 --> 21:36.280 But like we also think of the like mixed reality 21:36.280 --> 21:39.560 and quantum is like these two interesting, 21:39.560 --> 21:40.920 you know, potentially. 21:40.920 --> 21:41.800 Quantum computing. 21:41.800 --> 21:42.640 Yeah. 21:42.640 --> 21:44.520 Okay, so let's get crazy then. 21:44.520 --> 21:48.920 So you're talking about some futuristic things here. 21:48.920 --> 21:50.920 Well, the mixed reality Microsoft is really, 21:50.920 --> 21:52.600 it's not even futuristic, it's here. 21:52.600 --> 21:53.440 It is. 21:53.440 --> 21:54.280 Incredible stuff. 21:54.280 --> 21:56.680 And look, and it's having an impact right now. 21:56.680 --> 21:58.720 Like one of the more interesting things 21:58.720 --> 22:01.280 that's happened with mixed reality over the past 22:01.280 --> 22:04.120 couple of years that I didn't clearly see 22:04.120 --> 22:08.400 is that it's become the computing device 22:08.400 --> 22:13.160 for folks who, for doing their work 22:13.160 --> 22:16.040 who haven't used any computing device at all 22:16.040 --> 22:16.960 to do their work before. 22:16.960 --> 22:19.800 So technicians and service folks 22:19.800 --> 22:24.200 and people who are doing like machine maintenance 22:24.200 --> 22:25.280 on factory floors. 22:25.280 --> 22:28.760 So like they, you know, because they're mobile 22:28.760 --> 22:30.280 and like they're out in the world 22:30.280 --> 22:32.320 and they're working with their hands 22:32.320 --> 22:34.080 and, you know, sort of servicing these 22:34.080 --> 22:36.520 like very complicated things. 22:36.520 --> 22:39.440 They're, they don't use their mobile phone 22:39.440 --> 22:41.440 and like they don't carry a laptop with them. 22:41.440 --> 22:43.480 And, you know, they're not tethered to a desk. 22:43.480 --> 22:46.920 And so mixed reality, like where it's getting 22:46.920 --> 22:48.840 traction right now, where HoloLens is selling 22:48.840 --> 22:53.840 a lot of units is for these sorts of applications 22:53.880 --> 22:55.440 for these workers and it's become like, 22:55.440 --> 22:58.040 I mean, like the people love it. 22:58.040 --> 23:00.600 They're like, oh my God, like this is like, 23:00.600 --> 23:02.840 for them like the same sort of productivity boosts 23:02.840 --> 23:05.520 that, you know, like an office worker had 23:05.520 --> 23:08.200 when they got their first personal computer. 23:08.200 --> 23:09.800 Yeah, but you did mention, 23:09.800 --> 23:13.400 it's certainly obvious AI as a platform, 23:13.400 --> 23:15.560 but can we dig into it a little bit? 23:15.560 --> 23:18.320 How does AI begin to infuse some of the products 23:18.320 --> 23:19.480 in Microsoft? 23:19.480 --> 23:24.480 So currently providing training of, for example, 23:25.040 --> 23:26.760 neural networks in the cloud 23:26.760 --> 23:30.960 or providing pre trained models 23:30.960 --> 23:35.360 or just even providing computing resources 23:35.360 --> 23:37.520 and whatever different inference 23:37.520 --> 23:39.320 that you want to do using neural networks. 23:39.320 --> 23:40.160 Yep. 23:40.160 --> 23:43.560 Well, how do you think of AI infusing the, 23:43.560 --> 23:45.880 as a platform that Microsoft can provide? 23:45.880 --> 23:48.320 Yeah, I mean, I think it's, it's super interesting. 23:48.320 --> 23:49.560 It's like everywhere. 23:49.560 --> 23:54.560 And like we run these, we run these review meetings now 23:54.560 --> 23:59.560 where it's me and Satya and like members of Satya's 24:01.480 --> 24:04.600 leadership team and like a cross functional group 24:04.600 --> 24:06.200 of folks across the entire company 24:06.200 --> 24:11.200 who are working on like either AI infrastructure 24:11.840 --> 24:15.520 or like have some substantial part of their, 24:16.480 --> 24:21.480 of their product work using AI in some significant way. 24:21.480 --> 24:23.440 Now, the important thing to understand is like, 24:23.440 --> 24:27.040 when you think about like how the AI is going to manifest 24:27.040 --> 24:29.600 in like an experience for something 24:29.600 --> 24:30.760 that's going to make it better, 24:30.760 --> 24:35.760 like I think you don't want the AI in this 24:35.760 --> 24:37.760 to be the first order thing. 24:37.760 --> 24:40.600 It's like whatever the product is and like the thing 24:40.600 --> 24:42.440 that is trying to help you do, 24:42.440 --> 24:44.560 like the AI just sort of makes it better. 24:44.560 --> 24:46.840 And you know, this is a gross exaggeration, 24:46.840 --> 24:50.680 but like I, yeah, people get super excited about it. 24:50.680 --> 24:53.280 They're super excited about like where the AI is showing up 24:53.280 --> 24:55.440 in products and I'm like, do you get that excited 24:55.440 --> 24:59.880 about like where you're using a hash table like in your code? 24:59.880 --> 25:03.200 Like it's just another, it's a very interesting 25:03.200 --> 25:05.800 programming tool, but it's sort of like it's an engineering 25:05.800 --> 25:09.560 tool and so like it shows up everywhere. 25:09.560 --> 25:12.920 So like we've got dozens and dozens of features now 25:12.920 --> 25:17.400 in office that are powered by like fairly sophisticated 25:17.400 --> 25:22.200 machine learning, our search engine wouldn't work at all 25:22.200 --> 25:24.840 if you took the machine learning out of it. 25:24.840 --> 25:28.560 The like increasingly, you know, 25:28.560 --> 25:33.560 things like content moderation on our Xbox and xCloud 25:34.800 --> 25:35.960 platform. 25:37.000 --> 25:39.160 When you mean moderation to me, like the recommender 25:39.160 --> 25:41.760 is like showing what you want to look at next. 25:41.760 --> 25:44.000 No, no, no, it's like anti bullying stuff. 25:44.000 --> 25:47.040 So the usual social network stuff that you have to deal with. 25:47.040 --> 25:47.880 Yeah, correct. 25:47.880 --> 25:50.080 But it's like really it's targeted, 25:50.080 --> 25:52.280 it's targeted towards a gaming audience. 25:52.280 --> 25:55.320 So it's like a very particular type of thing where, 25:55.320 --> 25:59.480 you know, the the line between playful banter 25:59.480 --> 26:02.280 and like legitimate bullying is like a subtle one. 26:02.280 --> 26:06.080 And like you have to, it's sort of tough. 26:06.080 --> 26:09.080 Like I have, I love to, if we could dig into it 26:09.080 --> 26:11.720 because you're also, you led the engineering efforts 26:11.720 --> 26:14.920 of LinkedIn and if we look at, 26:14.920 --> 26:17.640 if we look at LinkedIn as a social network 26:17.640 --> 26:21.760 and if we look at the Xbox gaming as the social components, 26:21.760 --> 26:24.840 the very different kinds of, I imagine communication 26:24.840 --> 26:26.880 going on on the two platforms, right? 26:26.880 --> 26:29.520 And the line in terms of bullying and so on 26:29.520 --> 26:31.480 is different on the two platforms. 26:31.480 --> 26:33.480 So how do you, I mean, 26:33.480 --> 26:36.240 such a fascinating philosophical discussion 26:36.240 --> 26:37.240 of where that line is. 26:37.240 --> 26:39.840 I don't think anyone knows the right answer. 26:39.840 --> 26:42.040 Twitter folks are under fire now, 26:42.040 --> 26:45.120 Jack at Twitter for trying to find that line. 26:45.120 --> 26:46.920 Nobody knows what that line is, 26:46.920 --> 26:51.720 but how do you try to find the line for, 26:52.480 --> 26:57.480 you know, trying to prevent abusive behavior 26:58.040 --> 27:00.200 and at the same time let people be playful 27:00.200 --> 27:02.880 and joke around and that kind of thing. 27:02.880 --> 27:04.640 I think in a certain way, like, you know, 27:04.640 --> 27:09.640 if you have what I would call vertical social networks, 27:09.640 --> 27:12.200 it gets to be a little bit easier. 27:12.200 --> 27:14.440 So like if you have a clear notion 27:14.440 --> 27:17.960 of like what your social network should be used for 27:17.960 --> 27:22.280 or like what you are designing a community around, 27:22.280 --> 27:25.800 then you don't have as many dimensions 27:25.800 --> 27:28.960 to your sort of content safety problem 27:28.960 --> 27:33.720 as, you know, as you do in a general purpose platform. 27:33.720 --> 27:37.520 I mean, so like on LinkedIn, 27:37.520 --> 27:39.920 like the whole social network is about 27:39.920 --> 27:41.560 connecting people with opportunity, 27:41.560 --> 27:43.160 whether it's helping them find a job 27:43.160 --> 27:46.280 or to, you know, sort of find mentors 27:46.280 --> 27:49.320 or to, you know, sort of help them 27:49.320 --> 27:52.120 like find their next sales lead 27:52.120 --> 27:56.160 or to just sort of allow them to broadcast 27:56.160 --> 27:59.440 their, you know, sort of professional identity 27:59.440 --> 28:04.440 to their network of peers and collaborators 28:04.440 --> 28:05.880 and, you know, sort of professional community. 28:05.880 --> 28:07.400 Like that is, I mean, like in some ways, 28:07.400 --> 28:08.960 like that's very, very broad, 28:08.960 --> 28:12.480 but in other ways, it's sort of, you know, it's narrow. 28:12.480 --> 28:17.480 And so like you can build AIs like machine learning systems 28:18.360 --> 28:23.360 that are, you know, capable with those boundaries 28:23.360 --> 28:26.200 of making better automated decisions about like, 28:26.200 --> 28:28.240 what is, you know, sort of inappropriate 28:28.240 --> 28:30.440 and offensive comment or dangerous comment 28:30.440 --> 28:31.920 or illegal content. 28:31.920 --> 28:34.800 When you have some constraints, 28:34.800 --> 28:37.400 you know, same thing with, you know, 28:37.400 --> 28:40.880 same thing with like the gaming social network. 28:40.880 --> 28:42.680 So for instance, like it's about playing games, 28:42.680 --> 28:44.880 about having fun and like the thing 28:44.880 --> 28:47.240 that you don't want to have happen on the platform. 28:47.240 --> 28:49.160 It's why bullying is such an important thing. 28:49.160 --> 28:50.600 Like bullying is not fun. 28:50.600 --> 28:53.400 So you want to do everything in your power 28:53.400 --> 28:56.240 to encourage that not to happen. 28:56.240 --> 29:00.320 And yeah, but I think that's a really important thing 29:00.320 --> 29:03.920 but I think it's sort of a tough problem in general. 29:03.920 --> 29:05.280 It's one where I think, you know, 29:05.280 --> 29:07.120 eventually we're gonna have to have 29:09.120 --> 29:13.800 some sort of clarification from our policy makers 29:13.800 --> 29:17.400 about what it is that we should be doing, 29:17.400 --> 29:20.880 like where the lines are, because it's tough. 29:20.880 --> 29:23.760 Like you don't, like in democracy, right? 29:23.760 --> 29:26.680 Like you don't want, you want some sort 29:26.680 --> 29:28.880 of democratic involvement. 29:28.880 --> 29:30.440 Like people should have a say 29:30.440 --> 29:34.680 in like where the lines are drawn. 29:34.680 --> 29:36.920 Like you don't want a bunch of people 29:36.920 --> 29:39.480 making like unilateral decisions. 29:39.480 --> 29:43.120 And like we are in a state right now 29:43.120 --> 29:44.760 for some of these platforms where you actually 29:44.760 --> 29:46.280 do have to make unilateral decisions 29:46.280 --> 29:48.640 where the policy making isn't gonna happen fast enough 29:48.640 --> 29:52.520 in order to like prevent very bad things from happening. 29:52.520 --> 29:55.200 But like we need the policy making side of that 29:55.200 --> 29:58.480 to catch up I think as quickly as possible 29:58.480 --> 30:00.680 because you want that whole process 30:00.680 --> 30:02.000 to be a democratic thing, 30:02.000 --> 30:05.760 not a, you know, not some sort of weird thing 30:05.760 --> 30:08.040 where you've got a non representative group 30:08.040 --> 30:10.440 of people making decisions that have, you know, 30:10.440 --> 30:12.520 like national and global impact. 30:12.520 --> 30:14.720 And it's fascinating because the digital space 30:14.720 --> 30:17.520 is different than the physical space 30:17.520 --> 30:19.800 in which nations and governments were established. 30:19.800 --> 30:23.960 And so what policy looks like globally, 30:23.960 --> 30:25.760 what bullying looks like globally, 30:25.760 --> 30:28.360 what healthy communication looks like globally 30:28.360 --> 30:31.920 is an open question and we're all figuring it out together. 30:31.920 --> 30:32.760 Which is fascinating. 30:32.760 --> 30:37.160 Yeah, I mean with, you know, sort of fake news for instance 30:37.160 --> 30:42.160 and deep fakes and fake news generated by humans. 30:42.320 --> 30:44.600 Yeah, so we can talk about deep fakes. 30:44.600 --> 30:46.120 Like I think that is another like, you know, 30:46.120 --> 30:48.280 sort of very interesting level of complexity. 30:48.280 --> 30:51.480 But like if you think about just the written word, right? 30:51.480 --> 30:54.400 Like we have, you know, we invented Papyrus 30:54.400 --> 30:56.760 what 3000 years ago where we, you know, 30:56.760 --> 31:01.160 you could sort of put word on paper. 31:01.160 --> 31:06.160 And then 500 years ago, like we get the printing press 31:07.240 --> 31:11.480 like where the word gets a little bit more ubiquitous. 31:11.480 --> 31:14.600 And then like you really, really didn't get ubiquitous 31:14.600 --> 31:18.400 printed word until the end of the 19th century 31:18.400 --> 31:20.720 when the offset press was invented. 31:20.720 --> 31:22.360 And then, you know, just sort of explodes 31:22.360 --> 31:25.360 and like, you know, the cross product of that 31:25.360 --> 31:28.960 and the industrial revolutions need 31:28.960 --> 31:32.880 for educated citizens resulted in like 31:32.880 --> 31:34.720 this rapid expansion of literacy 31:34.720 --> 31:36.000 and the rapid expansion of the word. 31:36.000 --> 31:39.680 But like we had 3000 years up to that point 31:39.680 --> 31:44.040 to figure out like how to, you know, like what's, 31:44.040 --> 31:46.880 what's journalism, what's editorial integrity? 31:46.880 --> 31:50.120 Like what's, you know, what's scientific peer review? 31:50.120 --> 31:52.840 And so like you built all of this mechanism 31:52.840 --> 31:57.080 to like try to filter through all of the noise 31:57.080 --> 32:00.600 that the technology made possible to like, you know, 32:00.600 --> 32:04.000 sort of getting to something that society could cope with. 32:04.000 --> 32:06.600 And like, if you think about just the piece, 32:06.600 --> 32:09.800 the PC didn't exist 50 years ago. 32:09.800 --> 32:11.800 And so in like this span of, you know, 32:11.800 --> 32:16.160 like half a century, like we've gone from no digital, 32:16.160 --> 32:18.320 you know, no ubiquitous digital technology 32:18.320 --> 32:21.080 to like having a device that sits in your pocket 32:21.080 --> 32:23.760 where you can sort of say whatever is on your mind 32:23.760 --> 32:26.800 to like what would Mary have 32:26.800 --> 32:31.800 and Mary Meeker just released her new like slide deck last week. 32:32.440 --> 32:37.360 You know, we've got 50% penetration of the internet 32:37.360 --> 32:38.520 to the global population. 32:38.520 --> 32:40.280 Like there are like three and a half billion people 32:40.280 --> 32:41.720 who are connected now. 32:41.720 --> 32:43.720 So it's like, it's crazy, crazy. 32:43.720 --> 32:45.000 They're like inconceivable, 32:45.000 --> 32:46.480 like how fast all of this happened. 32:46.480 --> 32:48.720 So, you know, it's not surprising 32:48.720 --> 32:51.000 that we haven't figured out what to do yet, 32:51.000 --> 32:55.640 but like we gotta really like lean into this set of problems 32:55.640 --> 33:00.200 because like we basically have three millennia worth of work 33:00.200 --> 33:02.520 to do about how to deal with all of this 33:02.520 --> 33:05.800 and like probably what amounts to the next decade 33:05.800 --> 33:07.040 worth of time. 33:07.040 --> 33:09.960 So since we're on the topic of tough, you know, 33:09.960 --> 33:11.600 tough challenging problems, 33:11.600 --> 33:15.200 let's look at more on the tooling side in AI 33:15.200 --> 33:18.440 that Microsoft is looking at as face recognition software. 33:18.440 --> 33:21.840 So there's a lot of powerful positive use cases 33:21.840 --> 33:24.240 for face recognition, but there's some negative ones 33:24.240 --> 33:27.200 and we're seeing those in different governments 33:27.200 --> 33:28.160 in the world. 33:28.160 --> 33:30.240 So how do you, how does Microsoft think 33:30.240 --> 33:33.880 about the use of face recognition software 33:33.880 --> 33:38.880 as a platform in governments and companies? 33:39.400 --> 33:42.280 Yeah, how do we strike an ethical balance here? 33:42.280 --> 33:47.280 Yeah, I think we've articulated a clear point of view. 33:47.280 --> 33:51.840 So Brad Smith wrote a blog post last fall, 33:51.840 --> 33:54.120 I believe that sort of like outline, 33:54.120 --> 33:57.000 like very specifically what, you know, 33:57.000 --> 33:59.280 what our point of view is there. 33:59.280 --> 34:02.240 And, you know, I think we believe that there are certain uses 34:02.240 --> 34:04.680 to which face recognition should not be put 34:04.680 --> 34:09.160 and we believe again that there's a need for regulation there. 34:09.160 --> 34:12.440 Like the government should like really come in and say 34:12.440 --> 34:15.720 that, you know, this is where the lines are. 34:15.720 --> 34:18.600 And like we very much wanted to like figuring out 34:18.600 --> 34:20.680 where the lines are should be a democratic process. 34:20.680 --> 34:23.240 But in the short term, like we've drawn some lines 34:23.240 --> 34:26.640 where, you know, we push back against uses 34:26.640 --> 34:29.440 of face recognition technology. 34:29.440 --> 34:32.480 You know, like this city of San Francisco, for instance, 34:32.480 --> 34:36.480 I think has completely outlawed any government agency 34:36.480 --> 34:39.560 from using face recognition tech. 34:39.560 --> 34:44.560 And like that may prove to be a little bit overly broad. 34:44.560 --> 34:48.840 But for like certain law enforcement things, 34:48.840 --> 34:53.840 like you really, I would personally rather be overly 34:54.040 --> 34:57.400 sort of cautious in terms of restricting use of it 34:57.400 --> 34:58.920 until like we have, you know, 34:58.920 --> 35:02.160 sort of defined a reasonable, you know, 35:02.160 --> 35:04.880 democratically determined regulatory framework 35:04.880 --> 35:08.840 for like where we could and should use it. 35:08.840 --> 35:10.880 And, you know, the other thing there is 35:11.960 --> 35:14.000 like we've got a bunch of research that we're doing 35:14.000 --> 35:18.400 and a bunch of progress that we've made on bias there. 35:18.400 --> 35:20.880 And like there are all sorts of like weird biases 35:20.880 --> 35:23.640 that these models can have like all the way 35:23.640 --> 35:26.920 from like the most noteworthy one where, you know, 35:26.920 --> 35:31.680 you may have underrepresented minorities 35:31.680 --> 35:34.680 who are like underrepresented in the training data. 35:34.680 --> 35:39.240 And then you start learning like strange things. 35:39.240 --> 35:42.160 But like they're even, you know, other weird things 35:42.160 --> 35:46.480 like we've, I think we've seen in the public research 35:46.480 --> 35:49.520 like models can learn strange things 35:49.520 --> 35:54.520 like all doctors or men for instance. 35:54.520 --> 35:59.520 Yeah, I mean, and so like it really is a thing where 36:00.760 --> 36:03.600 it's very important for everybody 36:03.600 --> 36:08.440 who is working on these things before they push publish, 36:08.440 --> 36:12.800 they launch the experiment, they, you know, push the code 36:12.800 --> 36:17.120 to, you know, online or they even publish the paper 36:17.120 --> 36:20.040 that they are at least starting to think 36:20.040 --> 36:25.040 about what some of the potential negative consequences 36:25.040 --> 36:25.880 are some of this stuff. 36:25.880 --> 36:29.040 I mean, this is where, you know, like the deep fake stuff 36:29.040 --> 36:32.360 I find very worrisome just because 36:32.360 --> 36:37.360 they're going to be some very good beneficial uses 36:39.800 --> 36:44.800 of like GAN generated imagery. 36:46.080 --> 36:48.440 And like, and funny enough, like one of the places 36:48.440 --> 36:52.920 where it's actually useful is we're using the technology 36:52.920 --> 36:57.920 right now to generate synthetic, synthetic visual data 36:58.640 --> 37:01.160 for training some of the face recognition models 37:01.160 --> 37:03.440 to get rid of the bias. 37:03.440 --> 37:05.800 So like that's one like super good use of the tech, 37:05.800 --> 37:09.640 but like, you know, it's getting good enough now 37:09.640 --> 37:12.320 where, you know, it's going to sort of challenge 37:12.320 --> 37:15.400 a normal human beings ability to like now you're just sort 37:15.400 --> 37:19.320 of say like it's very expensive for someone 37:19.320 --> 37:23.280 to fabricate a photorealistic fake video. 37:24.200 --> 37:26.920 And like GANs are going to make it fantastically cheap 37:26.920 --> 37:30.440 to fabricate a photorealistic fake video. 37:30.440 --> 37:33.920 And so like what you assume you can sort of trust 37:33.920 --> 37:38.400 is true versus like be skeptical about is about to change. 37:38.400 --> 37:40.560 And like we're not ready for it, I don't think. 37:40.560 --> 37:42.000 The nature of truth, right? 37:42.000 --> 37:46.360 That's, it's also exciting because I think both you 37:46.360 --> 37:49.600 and I probably would agree that the way to solve, 37:49.600 --> 37:52.080 to take on that challenge is with technology. 37:52.080 --> 37:52.920 Yeah. Right. 37:52.920 --> 37:56.800 There's probably going to be ideas of ways to verify 37:56.800 --> 38:00.800 which kind of video is legitimate, which kind is not. 38:00.800 --> 38:03.880 So to me, that's an exciting possibility. 38:03.880 --> 38:07.160 Most likely for just the comedic genius 38:07.160 --> 38:10.960 that the internet usually creates with these kinds of videos. 38:10.960 --> 38:13.960 And hopefully will not result in any serious harm. 38:13.960 --> 38:17.680 Yeah. And it could be, you know, like I think 38:17.680 --> 38:22.680 we will have technology to that may be able to detect 38:23.040 --> 38:24.440 whether or not something's fake or real. 38:24.440 --> 38:29.440 Although the fakes are pretty convincing 38:30.160 --> 38:34.360 even like when you subject them to machine scrutiny. 38:34.360 --> 38:37.800 But, you know, we also have these increasingly 38:37.800 --> 38:40.520 interesting social networks, you know, 38:40.520 --> 38:45.520 that are under fire right now for some of the bad things 38:45.800 --> 38:46.640 that they do. 38:46.640 --> 38:47.720 Like one of the things you could choose to do 38:47.720 --> 38:51.760 with a social network is like you could, 38:51.760 --> 38:55.560 you could use crypto and the networks 38:55.560 --> 38:59.960 to like have content signed where you could have a like 38:59.960 --> 39:02.160 full chain of custody that accompanied 39:02.160 --> 39:03.920 every piece of content. 39:03.920 --> 39:06.800 So like when you're viewing something 39:06.800 --> 39:09.640 and like you want to ask yourself like how, you know, 39:09.640 --> 39:11.040 how much can I trust this? 39:11.040 --> 39:12.400 Like you can click something 39:12.400 --> 39:15.640 and like have a verified chain of custody that shows like, 39:15.640 --> 39:19.040 oh, this is coming from, you know, from this source. 39:19.040 --> 39:24.040 And it's like signed by like someone whose identity I trust. 39:24.080 --> 39:25.400 Yeah, I think having that, you know, 39:25.400 --> 39:28.040 having that chain of custody like being able to like say, 39:28.040 --> 39:31.200 oh, here's this video, like it may or may not 39:31.200 --> 39:33.760 been produced using some of this deep fake technology. 39:33.760 --> 39:35.640 But if you've got a verified chain of custody 39:35.640 --> 39:37.800 where you can sort of trace it all the way back 39:37.800 --> 39:39.960 to an identity and you can decide whether or not 39:39.960 --> 39:41.520 like I trust this identity. 39:41.520 --> 39:43.360 Like, oh no, this is really from the White House 39:43.360 --> 39:45.480 or like this is really from the, you know, 39:45.480 --> 39:48.840 the office of this particular presidential candidate 39:48.840 --> 39:50.960 or it's really from, you know, 39:50.960 --> 39:55.520 Jeff Wiener CEO of LinkedIn or Satya Nadella CEO of Microsoft. 39:55.520 --> 39:58.400 Like that might be like one way 39:58.400 --> 39:59.960 that you can solve some of the problems. 39:59.960 --> 40:01.800 So like that's not the super high tech. 40:01.800 --> 40:04.480 Like we've had all of this technology forever. 40:04.480 --> 40:06.720 And but I think you're right. 40:06.720 --> 40:11.120 Like it has to be some sort of technological thing 40:11.120 --> 40:15.840 because the underlying tech that is used to create this 40:15.840 --> 40:18.800 is not going to do anything but get better over time 40:18.800 --> 40:21.160 and the genie is sort of out of the bottle. 40:21.160 --> 40:22.800 There's no stuffing it back in. 40:22.800 --> 40:24.520 And there's a social component 40:24.520 --> 40:26.600 which I think is really healthy for democracy 40:26.600 --> 40:30.200 where people will be skeptical about the thing they watch. 40:30.200 --> 40:31.040 Yeah. 40:31.040 --> 40:34.160 In general, so, you know, which is good. 40:34.160 --> 40:37.280 Skepticism in general is good for your personal content. 40:37.280 --> 40:40.400 So deep fakes in that sense are creating 40:40.400 --> 40:44.800 global skepticism about can they trust what they read? 40:44.800 --> 40:46.880 It encourages further research. 40:46.880 --> 40:48.840 I come from the Soviet Union 40:49.800 --> 40:53.320 where basically nobody trusted the media 40:53.320 --> 40:55.120 because you knew it was propaganda. 40:55.120 --> 40:59.160 And that kind of skepticism encouraged further research 40:59.160 --> 41:02.360 about ideas supposed to just trusting anyone's source. 41:02.360 --> 41:05.440 Well, like I think it's one of the reasons why the, 41:05.440 --> 41:09.440 you know, the scientific method and our apparatus 41:09.440 --> 41:11.480 of modern science is so good. 41:11.480 --> 41:15.360 Like because you don't have to trust anything. 41:15.360 --> 41:18.520 Like you, like the whole notion of, you know, 41:18.520 --> 41:21.320 like modern science beyond the fact that, you know, 41:21.320 --> 41:23.440 this is a hypothesis and this is an experiment 41:23.440 --> 41:24.840 to test the hypothesis. 41:24.840 --> 41:27.360 And, you know, like this is a peer review process 41:27.360 --> 41:30.080 for scrutinizing published results. 41:30.080 --> 41:33.280 But like stuff's also supposed to be reproducible. 41:33.280 --> 41:35.240 So like, you know, it's been vetted by this process, 41:35.240 --> 41:38.000 but like you also are expected to publish enough detail 41:38.000 --> 41:41.480 where, you know, if you are sufficiently skeptical 41:41.480 --> 41:44.720 of the thing, you can go try to like reproduce it yourself. 41:44.720 --> 41:47.560 And like, I don't know what it is. 41:47.560 --> 41:49.920 Like, I think a lot of engineers are like this 41:49.920 --> 41:52.600 where like, you know, sort of this, like your brain 41:52.600 --> 41:55.520 is sort of wired for skepticism. 41:55.520 --> 41:58.000 Like you don't just first order trust everything 41:58.000 --> 42:00.040 that you see and encounter. 42:00.040 --> 42:02.560 And like you're sort of curious to understand, 42:02.560 --> 42:04.480 you know, the next thing. 42:04.480 --> 42:09.080 But like, I think it's an entirely healthy thing. 42:09.080 --> 42:12.280 And like we need a little bit more of that right now. 42:12.280 --> 42:16.200 So I'm not a large business owner. 42:16.200 --> 42:23.200 So I'm just, I'm just a huge fan of many of Microsoft products. 42:23.200 --> 42:25.360 I mean, I still, actually in terms of, 42:25.360 --> 42:27.000 I generate a lot of graphics and images 42:27.000 --> 42:28.640 and I still use PowerPoint to do that. 42:28.640 --> 42:30.440 It beats Illustrator for me. 42:30.440 --> 42:34.480 Even professional sort of, it's fascinating. 42:34.480 --> 42:39.560 So I wonder what is the future of, let's say, 42:39.560 --> 42:41.920 windows and office look like? 42:41.920 --> 42:43.840 Is do you see it? 42:43.840 --> 42:45.880 I mean, I remember looking forward to XP. 42:45.880 --> 42:48.200 Was it exciting when XP was released? 42:48.200 --> 42:51.080 Just like you said, I don't remember when 95 was released. 42:51.080 --> 42:53.800 But XP for me was a big celebration. 42:53.800 --> 42:56.000 And when 10 came out, I was like, 42:56.000 --> 42:58.040 okay, well, it's nice, it's a nice improvement. 42:58.040 --> 43:02.600 But so what do you see the future of these products? 43:02.600 --> 43:04.640 You know, I think there's a bunch of excitement. 43:04.640 --> 43:07.160 I mean, on the office front, 43:07.160 --> 43:13.440 there's going to be this like increasing productivity 43:13.440 --> 43:17.080 wins that are coming out of some of these AI powered features 43:17.080 --> 43:19.000 that are coming, like the products will sort of get 43:19.000 --> 43:21.120 smarter and smarter in like a very subtle way. 43:21.120 --> 43:24.120 Like there's not going to be this big bang moment 43:24.120 --> 43:27.080 where, you know, like Clippy is going to reemerge 43:27.080 --> 43:27.960 and it's going to be... 43:27.960 --> 43:28.680 Wait a minute. 43:28.680 --> 43:30.520 Okay, well, I have to wait, wait, wait. 43:30.520 --> 43:31.960 It's Clippy coming back. 43:31.960 --> 43:34.560 Well, quite seriously. 43:34.560 --> 43:37.920 So injection of AI, there's not much, 43:37.920 --> 43:39.040 or at least I'm not familiar, 43:39.040 --> 43:41.200 sort of assistive type of stuff going on 43:41.200 --> 43:43.600 inside the office products, 43:43.600 --> 43:47.600 like a Clippy style assistant, personal assistant. 43:47.600 --> 43:50.560 Do you think that there's a possibility 43:50.560 --> 43:52.000 of that in the future? 43:52.000 --> 43:54.680 So I think there are a bunch of like very small ways 43:54.680 --> 43:57.320 in which like machine learning power 43:57.320 --> 44:00.080 and assistive things are in the product right now. 44:00.080 --> 44:04.800 So there are a bunch of interesting things, 44:04.800 --> 44:09.280 like the auto response stuff's getting better and better 44:09.280 --> 44:12.160 and it's like getting to the point where, you know, 44:12.160 --> 44:14.960 it can auto respond with like, okay, 44:14.960 --> 44:19.080 let this person is clearly trying to schedule a meeting 44:19.080 --> 44:21.520 so it looks at your calendar and it automatically 44:21.520 --> 44:24.080 like tries to find like a time and a space 44:24.080 --> 44:26.240 that's mutually interesting. 44:26.240 --> 44:31.240 Like we have this notion of Microsoft search 44:33.520 --> 44:34.960 where it's like not just web search, 44:34.960 --> 44:38.200 but it's like search across like all of your information 44:38.200 --> 44:43.200 that's sitting inside of like your Office 365 tenant 44:43.320 --> 44:46.880 and like, you know, potentially in other products. 44:46.880 --> 44:49.680 And like we have this thing called the Microsoft Graph 44:49.680 --> 44:53.400 that is basically a API federator that, you know, 44:53.400 --> 44:57.960 sort of like gets you hooked up across the entire breadth 44:57.960 --> 44:59.760 of like all of the, you know, 44:59.760 --> 45:01.640 like what were information silos 45:01.640 --> 45:04.720 before they got woven together with the graph. 45:05.680 --> 45:07.880 Like that is like getting increasing 45:07.880 --> 45:09.160 with increasing effectiveness, 45:09.160 --> 45:11.280 sort of plumbed into the, 45:11.280 --> 45:13.120 into some of these auto response things 45:13.120 --> 45:15.840 where you're going to be able to see the system 45:15.840 --> 45:18.200 like automatically retrieve information for you. 45:18.200 --> 45:21.160 Like if, you know, like I frequently send out, 45:21.160 --> 45:24.080 you know, emails to folks where like I can't find a paper 45:24.080 --> 45:25.400 or a document or whatnot. 45:25.400 --> 45:26.840 There's no reason why the system won't be able 45:26.840 --> 45:27.680 to do that for you. 45:27.680 --> 45:29.560 And like, I think the, 45:29.560 --> 45:33.640 it's building towards like having things that look more 45:33.640 --> 45:37.880 like like a fully integrated, you know, assistant, 45:37.880 --> 45:40.720 but like you'll have a bunch of steps 45:40.720 --> 45:42.800 that you will see before you, 45:42.800 --> 45:45.120 like it will not be this like big bang thing 45:45.120 --> 45:47.400 where like Clippy comes back and you've got this like, 45:47.400 --> 45:49.360 you know, manifestation of, you know, 45:49.360 --> 45:52.000 like a fully, fully powered assistant. 45:53.320 --> 45:56.920 So I think that's, that's definitely coming out. 45:56.920 --> 45:58.680 Like all of the, you know, collaboration, 45:58.680 --> 46:00.720 co authoring stuff's getting better. 46:00.720 --> 46:02.200 You know, it's like really interesting. 46:02.200 --> 46:07.200 Like if you look at how we use the office product portfolio 46:08.320 --> 46:10.840 at Microsoft, like more and more of it is happening 46:10.840 --> 46:14.480 inside of like teams as a canvas. 46:14.480 --> 46:17.160 And like it's this thing where, you know, 46:17.160 --> 46:19.840 that you've got collaboration is like 46:19.840 --> 46:21.560 at the center of the product. 46:21.560 --> 46:26.560 And like we, we, we built some like really cool stuff 46:26.720 --> 46:29.440 that's some of, which is about to be open source 46:29.440 --> 46:33.120 that are sort of framework level things for doing, 46:33.120 --> 46:35.600 for doing co authoring. 46:35.600 --> 46:36.440 That's awesome. 46:36.440 --> 46:38.920 So in, is there a cloud component to that? 46:38.920 --> 46:41.880 So on the web or is it, 46:41.880 --> 46:43.640 forgive me if I don't already know this, 46:43.640 --> 46:45.600 but with office 365, 46:45.600 --> 46:48.480 we still, the collaboration we do, if we're doing Word, 46:48.480 --> 46:50.640 we're still sending the file around. 46:50.640 --> 46:51.480 No, no, no, no. 46:51.480 --> 46:53.400 So this is, 46:53.400 --> 46:55.240 we're already a little bit better than that. 46:55.240 --> 46:57.360 And like, you know, so like the fact that you're unaware 46:57.360 --> 46:59.120 of it means we've got a better job to do, 46:59.120 --> 47:01.960 like helping you discover, discover this stuff. 47:02.880 --> 47:06.360 But yeah, I mean, it's already like got a huge, 47:06.360 --> 47:07.200 huge cloud component. 47:07.200 --> 47:09.680 And like part of, you know, part of this framework stuff, 47:09.680 --> 47:12.640 I think we're calling it, like I, 47:12.640 --> 47:14.520 like we've been working on it for a couple of years. 47:14.520 --> 47:17.200 So like, I know the, the internal OLA code name for it, 47:17.200 --> 47:18.640 but I think when we launched it to build, 47:18.640 --> 47:20.720 it's called the fluid framework. 47:21.920 --> 47:25.080 And, but like what fluid lets you do is like, 47:25.080 --> 47:27.920 you can go into a conversation that you're having in teams 47:27.920 --> 47:30.280 and like reference, like part of a spreadsheet 47:30.280 --> 47:32.600 that you're working on, 47:32.600 --> 47:35.600 where somebody's like sitting in the Excel canvas, 47:35.600 --> 47:37.760 like working on the spreadsheet with a, you know, 47:37.760 --> 47:39.120 charter whatnot. 47:39.120 --> 47:42.000 And like, you can sort of embed like part of the spreadsheet 47:42.000 --> 47:43.240 in the team's conversation, 47:43.240 --> 47:46.520 where like you can dynamically update in like all 47:46.520 --> 47:49.400 of the changes that you're making to the, 47:49.400 --> 47:51.280 to this object or like, you know, 47:51.280 --> 47:54.680 coordinate and everything is sort of updating in real time. 47:54.680 --> 47:58.000 So like you can be in whatever canvas is most convenient 47:58.000 --> 48:00.400 for you to get your work done. 48:00.400 --> 48:03.400 So out of my own sort of curiosity as an engineer, 48:03.400 --> 48:06.280 I know what it's like to sort of lead a team 48:06.280 --> 48:08.280 of 10, 15 engineers. 48:08.280 --> 48:11.680 Microsoft has, I don't know what the numbers are, 48:11.680 --> 48:14.920 maybe 15, maybe 60,000 engineers, maybe 40. 48:14.920 --> 48:16.160 I don't know exactly what the number is. 48:16.160 --> 48:17.000 It's a lot. 48:17.000 --> 48:18.520 It's tens of thousands. 48:18.520 --> 48:20.640 Right. This is more than 10 or 15. 48:23.640 --> 48:28.640 I mean, you've led different sizes, 48:28.720 --> 48:30.560 mostly large sizes of engineers. 48:30.560 --> 48:33.840 What does it take to lead such a large group 48:33.840 --> 48:37.480 into a continue innovation, 48:37.480 --> 48:40.240 continue being highly productive 48:40.240 --> 48:43.200 and yet develop all kinds of new ideas 48:43.200 --> 48:45.120 and yet maintain like, what does it take 48:45.120 --> 48:49.000 to lead such a large group of brilliant people? 48:49.000 --> 48:52.080 I think the thing that you learn 48:52.080 --> 48:55.120 as you manage larger and larger scale 48:55.120 --> 48:57.920 is that there are three things 48:57.920 --> 49:00.480 that are like very, very important 49:00.480 --> 49:02.360 for big engineering teams. 49:02.360 --> 49:06.320 Like one is like having some sort of forethought 49:06.320 --> 49:09.840 about what it is that you're going to be building 49:09.840 --> 49:11.040 over large periods of time. 49:11.040 --> 49:11.880 Like not exactly. 49:11.880 --> 49:13.760 Like you don't need to know that like, 49:13.760 --> 49:16.440 I'm putting all my chips on this one product 49:16.440 --> 49:17.760 and like this is going to be the thing. 49:17.760 --> 49:21.440 But it's useful to know what sort of capabilities 49:21.440 --> 49:23.080 you think you're going to need to have 49:23.080 --> 49:24.720 to build the products of the future 49:24.720 --> 49:28.000 and then like invest in that infrastructure. 49:28.000 --> 49:31.520 Like whether, and I'm not just talking about storage systems 49:31.520 --> 49:33.480 or cloud APIs, it's also like, 49:33.480 --> 49:35.360 what is your development process look like? 49:35.360 --> 49:36.720 What tools do you want? 49:36.720 --> 49:39.560 Like what culture do you want to build 49:39.560 --> 49:42.760 around like how you're sort of collaborating together 49:42.760 --> 49:45.720 to like make complicated technical things? 49:45.720 --> 49:48.080 And so like having an opinion and investing in that 49:48.080 --> 49:50.480 is like, it just gets more and more important. 49:50.480 --> 49:54.520 And like the sooner you can get a concrete set of opinions, 49:54.520 --> 49:57.680 like the better you're going to be. 49:57.680 --> 50:01.600 Like you can wing it for a while at small scales. 50:01.600 --> 50:03.160 Like, you know, when you start a company, 50:03.160 --> 50:06.320 like you don't have to be like super specific about it. 50:06.320 --> 50:10.000 But like the biggest miseries that I've ever seen 50:10.000 --> 50:12.640 as an engineering leader are in places 50:12.640 --> 50:14.440 where you didn't have a clear enough opinion 50:14.440 --> 50:16.800 about those things soon enough. 50:16.800 --> 50:20.240 And then you just sort of go create a bunch of technical debt 50:20.240 --> 50:24.000 and like culture debt that is excruciatingly painful 50:24.000 --> 50:25.760 to clean up. 50:25.760 --> 50:28.640 So like that's one bundle of things. 50:28.640 --> 50:33.640 Like the other, you know, another bundle of things is 50:33.640 --> 50:37.440 like it's just really, really important to 50:38.960 --> 50:43.960 like have a clear mission that's not just some cute crap 50:45.520 --> 50:48.880 you say because like you think you should have a mission, 50:48.880 --> 50:52.880 but like something that clarifies for people 50:52.880 --> 50:55.680 like where it is that you're headed together. 50:57.160 --> 50:58.520 Like I know it's like probably 50:58.520 --> 51:00.320 like a little bit too popular right now, 51:00.320 --> 51:05.320 but Yval Harari's book, Sapiens, 51:07.240 --> 51:12.240 one of the central ideas in his book is that 51:12.440 --> 51:16.840 like storytelling is like the quintessential thing 51:16.840 --> 51:20.480 for coordinating the activities of large groups of people. 51:20.480 --> 51:22.320 Like once you get past Dunbar's number 51:23.360 --> 51:25.800 and like I've really, really seen that 51:25.800 --> 51:27.320 just managing engineering teams. 51:27.320 --> 51:32.080 Like you can just brute force things 51:32.080 --> 51:35.160 when you're less than 120, 150 folks 51:35.160 --> 51:37.520 where you can sort of know and trust 51:37.520 --> 51:40.920 and understand what the dynamics are between all the people. 51:40.920 --> 51:41.840 But like past that, 51:41.840 --> 51:45.440 like things just sort of start to catastrophically fail 51:45.440 --> 51:48.760 if you don't have some sort of set of shared goals 51:48.760 --> 51:50.480 that you're marching towards. 51:50.480 --> 51:52.960 And so like even though it sounds touchy feely 51:52.960 --> 51:55.640 and you know, like a bunch of technical people 51:55.640 --> 51:58.200 will sort of balk at the idea that like you need 51:58.200 --> 52:01.680 to like have a clear, like the missions 52:01.680 --> 52:03.560 like very, very, very important. 52:03.560 --> 52:04.640 Yval's right, right? 52:04.640 --> 52:07.520 Stories, that's how our society, 52:07.520 --> 52:09.360 that's the fabric that connects us all of us 52:09.360 --> 52:11.120 is these powerful stories. 52:11.120 --> 52:13.440 And that works for companies too, right? 52:13.440 --> 52:14.520 It works for everything. 52:14.520 --> 52:16.520 Like I mean, even down to like, you know, 52:16.520 --> 52:18.280 you sort of really think about like our currency 52:18.280 --> 52:19.960 for instance is a story. 52:19.960 --> 52:23.360 Our constitution is a story, our laws are story. 52:23.360 --> 52:27.840 I mean, like we believe very, very, very strongly in them 52:27.840 --> 52:29.960 and thank God we do. 52:29.960 --> 52:33.040 But like they are, they're just abstract things. 52:33.040 --> 52:34.000 Like they're just words. 52:34.000 --> 52:36.520 Like if we don't believe in them, they're nothing. 52:36.520 --> 52:39.440 And in some sense, those stories are platforms 52:39.440 --> 52:43.040 and the kinds some of which Microsoft is creating, right? 52:43.040 --> 52:46.360 Yeah, platforms in which we define the future. 52:46.360 --> 52:48.600 So last question, what do you, 52:48.600 --> 52:50.080 let's get philosophical maybe, 52:50.080 --> 52:51.480 bigger than even Microsoft. 52:51.480 --> 52:56.280 What do you think the next 2030 plus years 52:56.280 --> 53:00.120 looks like for computing, for technology, for devices? 53:00.120 --> 53:03.760 Do you have crazy ideas about the future of the world? 53:04.600 --> 53:06.400 Yeah, look, I think we, you know, 53:06.400 --> 53:09.480 we're entering this time where we've got, 53:10.640 --> 53:13.360 we have technology that is progressing 53:13.360 --> 53:15.800 at the fastest rate that it ever has. 53:15.800 --> 53:20.800 And you've got, you get some really big social problems 53:20.800 --> 53:25.800 like society scale problems that we have to tackle. 53:26.320 --> 53:28.720 And so, you know, I think we're gonna rise to the challenge 53:28.720 --> 53:30.560 and like figure out how to intersect 53:30.560 --> 53:32.400 like all of the power of this technology 53:32.400 --> 53:35.320 with all of the big challenges that are facing us, 53:35.320 --> 53:37.840 whether it's, you know, global warming, 53:37.840 --> 53:41.000 whether it's like the biggest remainder of the population 53:41.000 --> 53:46.000 boom is in Africa for the next 50 years or so. 53:46.800 --> 53:49.360 And like global warming is gonna make it increasingly 53:49.360 --> 53:52.600 difficult to feed the global population in particular, 53:52.600 --> 53:54.200 like in this place where you're gonna have 53:54.200 --> 53:56.600 like the biggest population boom. 53:57.720 --> 54:01.520 I think we, you know, like AI is gonna, 54:01.520 --> 54:03.560 like if we push it in the right direction, 54:03.560 --> 54:05.680 like it can do like incredible things 54:05.680 --> 54:10.160 to empower all of us to achieve our full potential 54:10.160 --> 54:15.160 and to, you know, like live better lives. 54:15.160 --> 54:20.160 But like that also means focus on like 54:20.520 --> 54:22.040 some super important things, 54:22.040 --> 54:23.960 like how can you apply it to healthcare 54:23.960 --> 54:28.960 to make sure that, you know, like our quality and cost of, 54:29.640 --> 54:32.080 and sort of ubiquity of health coverage 54:32.080 --> 54:35.080 is better and better over time. 54:35.080 --> 54:37.960 Like that's more and more important every day 54:37.960 --> 54:40.880 is like in the United States 54:40.880 --> 54:43.280 and like the rest of the industrialized world. 54:43.280 --> 54:45.720 So Western Europe, China, Japan, Korea, 54:45.720 --> 54:48.880 like you've got this population bubble 54:48.880 --> 54:52.880 of like aging working, you know, working age folks 54:52.880 --> 54:56.200 who are, you know, at some point over the next 20, 30 years 54:56.200 --> 54:58.000 they're gonna be largely retired 54:58.000 --> 55:00.160 and like you're gonna have more retired people 55:00.160 --> 55:01.200 than working age people. 55:01.200 --> 55:02.520 And then like you've got, you know, 55:02.520 --> 55:04.800 sort of natural questions about who's gonna take care 55:04.800 --> 55:07.120 of all the old folks and who's gonna do all the work. 55:07.120 --> 55:11.040 And the answers to like all of these sorts of questions 55:11.040 --> 55:13.200 like where you're sort of running into, you know, 55:13.200 --> 55:16.080 like constraints of the, you know, 55:16.080 --> 55:20.080 the world and of society has always been like 55:20.080 --> 55:23.000 what tech is gonna like help us get around this. 55:23.000 --> 55:26.360 You know, like when I was a kid in the 70s and 80s, 55:26.360 --> 55:29.800 like we talked all the time about like population boom, 55:29.800 --> 55:32.200 population boom, like we're gonna, 55:32.200 --> 55:34.360 like we're not gonna be able to like feed the planet. 55:34.360 --> 55:36.800 And like we were like right in the middle 55:36.800 --> 55:38.200 of the green revolution 55:38.200 --> 55:43.200 where like this massive technology driven increase 55:44.560 --> 55:47.520 and crop productivity like worldwide. 55:47.520 --> 55:49.320 And like some of that was like taking some of the things 55:49.320 --> 55:52.560 that we knew in the West and like getting them distributed 55:52.560 --> 55:55.760 to the, you know, to the developing world. 55:55.760 --> 55:59.360 And like part of it were things like, you know, 55:59.360 --> 56:03.280 just smarter biology like helping us increase. 56:03.280 --> 56:06.760 And like we don't talk about like, yeah, 56:06.760 --> 56:10.320 overpopulation anymore because like we can more or less, 56:10.320 --> 56:12.000 we sort of figured out how to feed the world. 56:12.000 --> 56:14.760 Like that's a technology story. 56:14.760 --> 56:19.480 And so like I'm super, super hopeful about the future 56:19.480 --> 56:24.080 and in the ways where we will be able to apply technology 56:24.080 --> 56:28.040 to solve some of these super challenging problems. 56:28.040 --> 56:31.360 Like I've, like one of the things 56:31.360 --> 56:34.680 that I'm trying to spend my time doing right now 56:34.680 --> 56:36.600 is trying to get everybody else to be hopeful 56:36.600 --> 56:38.720 as well because, you know, back to Harari, 56:38.720 --> 56:41.160 like we are the stories that we tell. 56:41.160 --> 56:44.320 Like if we, you know, if we get overly pessimistic right now 56:44.320 --> 56:49.320 about like the potential future of technology, like we, 56:49.320 --> 56:53.680 you know, like we may fail to fail to get all the things 56:53.680 --> 56:56.880 in place that we need to like have our best possible future. 56:56.880 --> 56:59.440 And that kind of hopeful optimism. 56:59.440 --> 57:03.160 I'm glad that you have it because you're leading large groups 57:03.160 --> 57:05.600 of engineers that are actually defining 57:05.600 --> 57:06.720 that are writing that story, 57:06.720 --> 57:08.320 that are helping build that future, 57:08.320 --> 57:10.000 which is super exciting. 57:10.000 --> 57:12.320 And I agree with everything you said, 57:12.320 --> 57:14.840 except I do hope Clippy comes back. 57:16.400 --> 57:17.760 We miss him. 57:17.760 --> 57:19.360 I speak for the people. 57:19.360 --> 57:21.800 So, Kellen, thank you so much for talking to me. 57:21.800 --> 57:22.640 Thank you so much for having me. 57:22.640 --> 57:43.640 It was a pleasure.